MSc Intelligent Communication Systems and Networks

Expected prior learning: It is helpful, but not essential, to have taken module EEE2040 – Communications Networks (EEE2040), or to have equivalent learning. Module purpose: This module deals with the three important processing stages of modern digital communication systems which are source coding for signal compression, channel error control coding for robust transmission and modulation for efficient digital interface with the available channel. The module is designed to provide basic-to-intermediate scale introduction of the subject at the UG level and the learning developed in this module can be enhanced further at relevant MEng / MSc level modules (EEEM017, EEEM030, EEEM031)

In this module, students will learn about the different key concepts and elements comprising a modern wireless communication system, e.g. signal, transmitter, receiver, wireless channel, as well as understand the primary objectives of communication systems, i.e. reliability and sprectrum efficiency. They will do so by engaging with the various types of teaching materials presented to them as well as participating in our MATLAB lab sessions where they will be given the opportunity to analyse and simulate radio propagation behaviours/coverage as well as to model and simulate key aspects of a simple wireless communication system.

This module offers a comprehensive introduction to Artificial Intelligence (AI) and Machine Learning (ML) with a focus on its applications in modern communication systems. By taking this module, the student builds a strong foundation of AI/ML starting from the mathematical basics (linear algebra, probability, optimization) and the main algorithms and models (e.g. Decision Trees, Support Vector Machines, Deep Neural Networks, etc.) to the modern generative models, and reinforcement learning. Through the coursework, the student will gain hands-on experience with key AI/ML models applied to modern communication systems. By the end of the module, the student will not only understand the theory of machine learning but also develop the practical skills needed to implement and evaluate models for real-world applications in communications.

Module purpose: Advances related to energy efficiency issues and cost reductions have resulted in the rapid growth and deployment of networked devices and sensing/actuation systems that connect the physical world with the cyber world. This evolving framework, now recognized as the Artificial Intelligence of Things (AIoT), integrates IoT technologies with artificial intelligence (AI) to enhance automation, intelligence, and decision-making. AIoT incorporates several cutting-edge technologies, including wireless sensor networks, pervasive systems, ambient intelligence, context awareness, distributed systems, and machine learning-driven analytics. Module Overview: The advanced AIoT module is designed to provide a comprehensive understanding of how machine communications , coupled with AI, contribute to creating smart artificial intelligence-driven environments, focusing on networking and communication systems. The module provides an overview of the key concepts and enabling technologies for AIoT. It encompasses a cross-layer approach, allowing students to explore the practical aspects of sensors, actuators, and mainly communication systems for AIoT across physical, media access, and network layers. This includes security considerations, satellite AIoT, positioning and tracking for industrial applications, AIoT Platforms (Hardware, Software), protocols and standards (e.g. 6LowPAN, ZigBee, CoAp), semantic technologies, and data and information processing mechanisms. Also, the module explores AI-driven methodologies such as ensemble learning, multi-armed bandits for sequential decision-making, and lightweight machine learning Mmodels for AIoT applications. These techniques enhance real-time data analysis, predictive maintenance, anomaly detection, and adaptive control while ensuring computational efficiency.

Radio frequency (RF) and microwave engineers require proficiency in a specific set of skills to in electronic circuitry that does not exist for other typical applications. Therefore, a good grounding in the electronics associated with RF and microwave devices and important underlying essential fundamentals are delivered for any form of RF or microwave engineering. The module will be important for other RF related modules such as EEEM044 RF System and Circuit Design and EEEM064 Microwave Design Techniques

Expected prior/parallel learning: BEng-level understanding of digital telecommunications systems. MEng students might have partly acquired this through study of EEE3006 – Digital Communications. Module purpose: Satellite communications are an important component of modern telecommunication systems. This module provides the student with an overall understanding of satellite communication systems, technologies and techniques and equips him/her with the design tools to enter employment in the sector. The main goal of this module is to design a satellite communication link to fix or mobile users given a specified quality of service (QoS). To do so, one needs to take into account both telecommunication and satellite related parameters. In this module, you will learn about the satellite payload and how it operates, what is in the earth station and what are the characteristics of the satellite to earth link. In particular, we clearly state the differences in design compared to the terrestrial communication systems We also study in some details the modern satellite networks and constellations. [EEE3006]: This module uses several techniques addressed in digital communications module such as coding and modulation. [EEEM032]: This module is a prerequisite for the advanced satellite communication techniques. [EEEM009],[EEEM059]: Even though other satellite applications such as earth observation or satellites for navigation and positioning are not addressed in this module, however, all such application will eventually need to stablish a communication line with earth. In this sense, this module is closely related to modules on space avionics and navigation, guidance and control.

IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: EEE3033 – RF and Microwave Fundamentals, or equivalent learning. Module purpose: Advanced communications systems and radar operate at RF and microwave frequencies. The design principles and circuit operation, underlying these systems, are quite different from those of electronics used in signal processing at baseband frequencies. This module will cover the key elements of RF and microwave system design as well as analysis concepts for a range of commonly used active circuits, including: oscillators, frequency synthesisers, amplifiers and mixers. The module will also cover the circuit design and operation of non-linear devices used in active circuits together with deployment considerations. This module will include and build on many of the concepts studied in EEE3033 RF and Microwave Fundamentals and address further advanced features of non linear RF devices and system optimisation. It is complementary to EEEM064 Microwave Design Techniques and also EEEM006 Antennas and Propagation.

The need for computational power and data storage continues to drive demand for more highly capable systems. Highly data intensive applications demand fast access to terabytes, petabytes, even exabytes of storage; processor intensive applications demand access to various types of processors in various configurations. Such applications are increasingly being developed in both scientific and industrial contexts and need to be variously scalable and supportable for large numbers of geographically distributed users. This module will provide insights into how Cloud Computing attempts to meet the varying needs of such applications.

Wireless networks (wide area cellular / satellite, local area residential / business, and ad-hoc / mesh) are an essential part of modern day communication / computing facilities. The network deployment, planning and management are the key issues ¿ all the network components must conform to the given hardware and software specifications in order that they can be interconnected and work successfully for the intended Quality of Service (QoS). This module introduces essential concepts about the network planning, network deployment and network management for a successful running of the network with a focus on software defined networking and virtualisation.

This module is aimed at forming essential professional skills and competences in responsible research and innovation for master level students studying in programmes relating to computer science and/or electronic engineering. It will therefore serve as an important initial module towards planning and executing the dissertation project through learning about literature reviewing and research methodologies. Furthermore, it will facilitate team building skills through identifying individual strengths and exercising capability together with use of artificial intelligence through group design work. This experience will also make the student aware of the challenges of working effectively with other people embracing equality, diversity and inclusion.

The module introduces general information and network security principles, challenges and goals and then focuses on main security mechanisms and protocols for protecting network communication across different layers of the Internet protocol stack. This will include discussion on various attacks on the networks, penetration testing tools and possible countermeasures to ensure protection of authentication, confidentiality and end-to-end security of communications. In labs students will be able to practice experience with various network security protocols and tools.

Expected prior learning: Module EEE2040 – Communications Networks or equivalent learning. Module purpose: The Internet is an important worldwide communications system; the module provides an in-depth treatment of current and evolving Internet protocols and standards, and the algorithms that underlie them. The module also permits further study on networking in modules such as EEEM018 Advanced Mobile Communication Systems, EEEM023 Network Service management and Control, EEEM032 Advanced Satellite Communication Techniques

Expected prior learning: Knowledge of basic properties of signals and related methods, including Fourier series, Fourier transforms, Laplace transforms, and convolution. BEng/MEng students might have acquired this through study of module EEE2035 Engineering Mathematics III and/or module EEE2033 Circuits, Control and Communications. MSc students might have acquired this through study of an undergraduate module on ¿Signals and Systems¿ or through independent study. Module purpose: This introductory course in Digital Signal Processing explores mathematical tools used to represent, analyse and design basic DSP systems. This module underpins many key areas of digital systems, including audio-visual technology, digital communications, control systems, and computer vision. This topic is therefore of paramount importance to any electronic engineer. This module EEE3045 provides the expected prior learning for the following module EEEM030 Speech & Audio Processing and Recognition. Taking module EEE3045 may also contribute to a deeper understanding of the following modules EEE3032 Computer Vision and Pattern Recognition, and EEEM071 Advanced Topics in Computer Vision and Deep Learning

Expected prior/parallel learning: This module covers advanced topics on satellite communications and networks, following the Satellite Communication fundamentals (EEEM031). An alternate module containing suitable prior learning is, Space System Design (EEE3040). Module purpose: This module covers advanced topics on satellite communications and networks. These networks are an important part of global information infrastructure providing broadcasting, mobile and broadband services to millions of homes and offices as well as disaster relieves and emergency communications services.

This module introduces students to some of the basic ideas and concepts that underlie the development of artificially intelligent machine systems. Teaches core AI materials for problem solving (search, logic, probabilistic methods, Perceptrons as the building block for ANNs) Focuses on core understanding and problem solving: suitable tools/methods for a problem using problem classes Provides a clear understanding of neural networks, back-propagation, RBFs, ANN learning and optimisation Provides a clear understanding of intelligent agents via search methods and introducing cost functions Provides a clear understanding of Bayes’ Rule, conditional probability and uncertainty reasoning Provides a clear understanding of knowledge capture, symbolic knowledge representation and logical reasoning from antiquity to Boule to first order predicate rules and representations. Provides opportunity to implement concepts during coursework.

IMPORTANT: The second assessment pattern is only applicable to the MSc Short Course Students Expected prior learning: None. Module purpose: Antennas and the propagation of radio on the physical layer (PHY) are a fundamental aspect of communications, space and radar as well as any other device that will radiate electromagnetic waves over an air interface. In order for wireless devices to operate and comply with suitable standards, it is important that they use a suitable antenna design, while also modelling the propagation environment the device may encounter is important for purposes of testing the radio transceiver, thus knowledge of propagation modelling is required to achieve this.

The purpose of this module is to equip students with advanced knowledge of key concepts in modern mobile and wireless communication systems, such as 5G, while also exploring emerging concepts that are likely to shape future technologies, including 6G. By completing this module, students will gain the expertise needed to work with wireless communications technologies in industry or to pursue further academic research in this field. The module bridges foundational knowledge in wireless communications with cutting-edge techniques and promising innovations that can enhance future communication systems, fostering cognitive and conceptual connections across these domains.

This module teaches cloud computing concepts and the security of the cloud platform to enable students to understand how to secure workloads on cloud. The topics including basic concepts and the core security services needed to secure workloads and the processing of sensitive data. To re-enforce learning, the module will require students to work in teams to configure the cloud platform using infrastructure automation.

Expected prior learning: Appropriate background knowledge related to the project topic. Module purpose: This is an individual student project module giving each masters student an opportunity to gain realistic experience in developing a solution to a problem from its inception to a demonstrable result. It provides a framework as well as a vehicle for exercising all key aspects of project work, from project specification, through literature and technology research, leading to project planning, problem solving as well as design and implementation, culminating in performance assessment, project demonstration, and project evaluation. It also provides a scope for gaining practical experience interpersonal skills, use of IT, project management, project reporting and project presentation. The project can be either of engineering design nature or have a research flavour. This module is complementary to all other taught modules in order to apply the learning gained into undertaking an independent piece of research and/or development.